Evidence map›Paper›PMID 29152612›Full record

ArticleThe 2010 ACM International Conference on Bioinformatics and Computational Biology : ACM-BCB 2010 : Niagara Falls, New York, U.S.A., August 2-4, 2010. ACM International Conference on Bioinformatics and Computational Biology (1st : 2010 :...2010

Genome-wide compatible SNP intervals and their properties.

Jeremy Wang, Fernando Pardo-Manual de Villena, Kyle J Moore, Wei Wang, Qi Zhang, Leonard McMillan

Abstract read
In one paragraph

Article in The 2010 ACM International Conference on Bioinformatics and Computational Biology : ACM-BCB 2010 : Niagara Falls, New York, U.S.A., August 2-4, 2010. ACM International Conference on Bioinformatics and Computational Biology (1st : 2010 :..., 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Domestication Shapes Recombination Patterns in Tomato.Molecular biology and evolution · 2022
    Article
  2. Article
  3. Article
  4. Article
  5. Informatics resources for the Collaborative Cross and related mouse populations.Mammalian genome : official journal of the International Mammalian Genome Society · 2015
    Review
  6. Article
  7. Deconstructing Mus gemischus: advances in understanding ancestry, structure, and variation in the genome of the laboratory mouse.Mammalian genome : official journal of the International Mammalian Genome Society · 2013
    Review
  8. Article
  9. Article
  10. Article
  11. Dynamic Visualization and Comparative Analysis of Multiple Collinear Genomic Data.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2011
    Article
  12. Article
  13. Inferring genome-wide mosaic structure.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2009
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jeremy WangDept. of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.
Fernando Pardo-Manual de VillenaDept. of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
Kyle J MooreDept. of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.
Wei WangDept. of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.
Qi ZhangDept. of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.
Leonard McMillanDept. of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.

Funding

UNC and PERLEGEN, IncP50GM076468 · NIGMS · JACKSON LABORATORY · PI PETKOV, PETKO M · 2006 to 2015
$31.0M
NIGMS NIH HHS P50 GM076468
6 · The paper itself

Abstract

Intraspecific genomes can be subdivided into blocks with limited diversity. Understanding the distribution and structure of these blocks will help to unravel many biological problems including the identification of genes associated with complex diseases, finding the ancestral origins of a given population, and localizing regions of historical recombination, gene conversion, and homoplasy. We present methods for partitioning a genome into blocks for which there are no apparent recombinations, thus providing parsimonious sets of compatible genome intervals based on the four-gamete test. Our contribution is a thorough analysis of the problem of dividing a genome into compatible intervals, in terms of its computational complexity, and by providing an achievable lower-bound on the minimal number of intervals required to cover an entire data set. In general, such minimal interval partitions are not unique. However, we identify properties that are common to every possible solution. We also define the notion of an interval set that achieves the interval lower-bound, yet maximizes interval overlap. We demonstrate algorithms for partitioning both haplotype data from inbred mice as well as outbred heterozygous genotype data using extensions of the standard four-gamete test. These methods allow our algorithms to be applied to a wide range of genomic data sets.

Identifiers

PMID29152612
PMCPMC5690570

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.